Grammar and dictionary based named- Entity Linking for knowledge extraction of evidence-based dietary recommendations
T. Eftimov, B. Koroušić Seljak, P. Korošec
8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management IC3K (KDIR 2016)
, Porto, Portugal, 9-11 November, 2016
In order to help people to follow the new knowledge about healthy diet that comes rapidly each day with the new published scientific reports, a grammar and dictionary based named-entity linking method is presented that can be used for knowledge extraction of evidence-based dietary recommendations. The method consists of two phases. The first one is a mix of entity detection and determination of a set of candidates for each entity, and the second one is a candidate selection. We evaluate our method using a corpus from dietary recommendations presented in one sentence provided by the World Health Organization and the U.S. National Library of Medicine. The corpus consists of 50 dietary recommendations and 10 sentences that are not related with dietary recommendations. For 47 out of 50 dietary recommendations the proposed method extract all the useful knowledge, and for remaining 3 only the information for one entity is missing. Due to the 10 sentences that are not dietary recommendation the method does not extract any entities, as expected.
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